{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:MZB4DPVWNEQH4ROJW6NSGVKVWP","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ce1087c6e63ebb571de24039448286aa69859e21926e8f3617af9037a376c9ab","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-13T22:29:23Z","title_canon_sha256":"81df6e7dcb4e3b19b6baace43b9149ed8ed3254d27f35224ac70723bda5ed0f1"},"schema_version":"1.0","source":{"id":"2411.09056","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2411.09056","created_at":"2026-07-05T09:35:19Z"},{"alias_kind":"arxiv_version","alias_value":"2411.09056v1","created_at":"2026-07-05T09:35:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2411.09056","created_at":"2026-07-05T09:35:19Z"},{"alias_kind":"pith_short_12","alias_value":"MZB4DPVWNEQH","created_at":"2026-07-05T09:35:19Z"},{"alias_kind":"pith_short_16","alias_value":"MZB4DPVWNEQH4ROJ","created_at":"2026-07-05T09:35:19Z"},{"alias_kind":"pith_short_8","alias_value":"MZB4DPVW","created_at":"2026-07-05T09:35:19Z"}],"graph_snapshots":[{"event_id":"sha256:4dd9c1a9814204fff28140e3a128d52eb3f6ef75955001a6a3f526bae50a2ea8","target":"graph","created_at":"2026-07-05T09:35:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2411.09056/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Ensuring fairness has emerged as one of the primary concerns in AI and its related algorithms. Over time, the field of machine learning fairness has evolved to address these issues. This paper provides an extensive overview of this field and introduces two formal frameworks to tackle open questions in machine learning fairness.\n  In one framework, operator-valued optimisation and min-max objectives are employed to address unfairness in time-series problems. This approach showcases state-of-the-art performance on the notorious COMPAS benchmark dataset, demonstrating its effectiveness in real-wo","authors_text":"Quan Zhou","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-13T22:29:23Z","title":"Optimisation Strategies for Ensuring Fairness in Machine Learning: With and Without Demographics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2411.09056","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:853282a6c23bb6ce4961a1d9e316b103e06794c57f20e65916dccbda2ed0dd91","target":"record","created_at":"2026-07-05T09:35:19Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ce1087c6e63ebb571de24039448286aa69859e21926e8f3617af9037a376c9ab","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-11-13T22:29:23Z","title_canon_sha256":"81df6e7dcb4e3b19b6baace43b9149ed8ed3254d27f35224ac70723bda5ed0f1"},"schema_version":"1.0","source":{"id":"2411.09056","kind":"arxiv","version":1}},"canonical_sha256":"6643c1beb669207e45c9b79b235555b3db4683c77402808559073bdc3fd438d3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6643c1beb669207e45c9b79b235555b3db4683c77402808559073bdc3fd438d3","first_computed_at":"2026-07-05T09:35:19.151095Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:35:19.151095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zrDyE/c6Xsa1uht7vHXlJ4pxzPUYHAXptNk8StGYvRQr2Xp4ykFJj3t7lbtOi2bPKCmo9unOf68vBEn6OXuxCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:35:19.151565Z","signed_message":"canonical_sha256_bytes"},"source_id":"2411.09056","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:853282a6c23bb6ce4961a1d9e316b103e06794c57f20e65916dccbda2ed0dd91","sha256:4dd9c1a9814204fff28140e3a128d52eb3f6ef75955001a6a3f526bae50a2ea8"],"state_sha256":"136b63690215490271551ba26e332ea085ed08eb8383b9395c3728c5d4655254"}